The Datadog AWS Lambda Library
Project description
datadog-lambda-python
Datadog Lambda Library for Python (3.6, 3.7, 3.8, and 3.9) enables enhanced Lambda metrics, distributed tracing, and custom metric submission from AWS Lambda functions.
IMPORTANT NOTE: AWS Lambda is expected to receive a breaking change on March 31, 2021. If you are using Datadog Python Lambda layer version 7 or below, please upgrade to the latest.
Installation
Follow the installation instructions, and view your function's enhanced metrics, traces and logs in Datadog.
Custom Metrics
Once installed, you should be able to submit custom metrics from your Lambda function.
Check out the instructions for submitting custom metrics from AWS Lambda functions.
Tracing
Once installed, you should be able to view your function's traces in Datadog, and your function's logs should be automatically connected to the traces.
For additional details on trace collection, take a look at collecting traces from AWS Lambda functions.
For additional details on trace and log connection, see connecting logs and traces.
For additional details on the tracer, check out the official documentation for Datadog trace client.
Enhanced Metrics
Once installed, you should be able to view enhanced metrics for your Lambda function in Datadog.
Check out the official documentation on Datadog Lambda enhanced metrics.
Advanced Configurations
Handler Wrapper
In order to instrument individual invocations, the Datadog Lambda library needs to wrap around your Lambda handler function. This is usually achieved by setting your function's handler to the Datadog handler function (datadog_lambda.handler.handler) and setting the environment variable DD_LAMBDA_HANDLER with your original handler function to be called by the Datadog handler.
If this method doesn't work for you, instead of setting the handler and the DD_LAMBDA_HANDLER environment variable, you can apply the Datadog Lambda library wrapper in your function code like below:
from datadog_lambda.wrapper import datadog_lambda_wrapper
@datadog_lambda_wrapper
def my_lambda_handle(event, context):
# your function code
Environment Variables
DD_FLUSH_TO_LOG
Set to true (recommended) to send custom metrics asynchronously (with no added latency to your Lambda function executions) through CloudWatch Logs with the help of Datadog Forwarder. Defaults to false. If set to false, you also need to set DD_API_KEY and DD_SITE.
DD_API_KEY
If DD_FLUSH_TO_LOG is set to false (not recommended), the Datadog API Key must be defined by setting one of the following environment variables:
- DD_API_KEY - the Datadog API Key in plain-text, NOT recommended
- DD_KMS_API_KEY - the KMS-encrypted API Key, requires the
kms:Decryptpermission - DD_API_KEY_SECRET_ARN - the Secret ARN to fetch API Key from the Secrets Manager, requires the
secretsmanager:GetSecretValuepermission (andkms:Decryptif using a customer managed CMK) - DD_API_KEY_SSM_NAME - the Parameter Name to fetch API Key from the Systems Manager Parameter Store, requires the
ssm:GetParameterpermission (andkms:Decryptif using a SecureString with a customer managed CMK)
You can also supply or override the API key at runtime (not recommended):
# Override DD API Key after importing datadog_lambda packages
from datadog import api
api._api_key = "MY_API_KEY"
DD_SITE
If DD_FLUSH_TO_LOG is set to false (not recommended), you must set DD_SITE. Possible values are datadoghq.com, datadoghq.eu, us3.datadoghq.com, us5.datadoghq.com, and ddog-gov.com. The default is datadoghq.com.
DD_LOGS_INJECTION
Inject Datadog trace id into logs for correlation if you are using a logging.Formatter in the default LambdaLoggerHandler by the Lambda runtime. Defaults to true.
DD_LOG_LEVEL
Set to debug enable debug logs from the Datadog Lambda Library. Defaults to info.
DD_ENHANCED_METRICS
Generate enhanced Datadog Lambda integration metrics, such as, aws.lambda.enhanced.invocations and aws.lambda.enhanced.errors. Defaults to true.
DD_LAMBDA_HANDLER
Your original Lambda handler.
DD_TRACE_ENABLED
Initialize the Datadog tracer when set to true. Defaults to false.
DD_MERGE_XRAY_TRACES
Set to true to merge the X-Ray trace and the Datadog trace, when using both the X-Ray and Datadog tracing. Defaults to false.
DD_TRACE_MANAGED_SERVICES (experimental)
Inferred Spans are spans that Datadog can create based on incoming event metadata.
Set DD_TRACE_MANAGED_SERVICES to true to infer spans based on Lambda events.
Inferring upstream spans is only supported if you are using the Datadog Lambda Extension.
Defaults to true.
Infers spans for:
- API Gateway REST events
- API Gateway WebSocket events
- HTTP API events
- SQS
- SNS (SNS messaged delivered via SQS are also supported)
- Kinesis Streams (if data is a JSON string or base64 encoded JSON string)
- EventBridge (custom events, where Details is a JSON string)
- S3
- DynamoDB
Opening Issues
If you encounter a bug with this package, we want to hear about it. Before opening a new issue, search the existing issues to avoid duplicates.
When opening an issue, include the Datadog Lambda Library version, Python version, and stack trace if available. In addition, include the steps to reproduce when appropriate.
You can also open an issue for a feature request.
Contributing
If you find an issue with this package and have a fix, please feel free to open a pull request following the procedures.
Community
For product feedback and questions, join the #serverless channel in the Datadog community on Slack.
License
Unless explicitly stated otherwise all files in this repository are licensed under the Apache License Version 2.0.
This product includes software developed at Datadog (https://www.datadoghq.com/). Copyright 2019 Datadog, Inc.
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